{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [多个子图表](04.08-Multiple-Subplots.ipynb) | [目录](Index.ipynb) | [自定义刻度](04.10-Customizing-Ticks.ipynb) >\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/wangyingsm/Python-Data-Science-Handbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open and Execute in Google Colaboratory\"></a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Text and Annotation\n",
    "\n",
    "# 文本和标注"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Creating a good visualization involves guiding the reader so that the figure tells a story.\n",
    "In some cases, this story can be told in an entirely visual manner, without the need for added text, but in others, small textual cues and labels are necessary.\n",
    "Perhaps the most basic types of annotations you will use are axes labels and titles, but the options go beyond this.\n",
    "Let's take a look at some data and how we might visualize and annotate it to help convey interesting information. We'll start by setting up the notebook for plotting and  importing the functions we will use:\n",
    "\n",
    "创建一个优秀的可视化图表的关键在于引导读者，让他们能理解图表所讲述的故事。在一些情况下，这个故事可以通过纯图像的方式表达，不需要额外添加文字，但是在另外一些情况中，图表需要文字的提示和标签才能将故事讲好。也许标注最基本的类型就是图表的标签和标题，但是其中的选项参数却有很多。让我们在本节中使用一些数据来创建可视化图表并标注这些图表来表达这些有趣的信息。首先还是需要将要用到的模块和包导入notebook："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Effect of Holidays on US Births\n",
    "\n",
    "## 例子：节假日对美国出生率的影响\n",
    "\n",
    "> Let's return to some data we worked with earler, in [\"Example: Birthrate Data\"](03.09-Pivot-Tables.ipynb#Example:-Birthrate-Data), where we generated a plot of average births over the course of the calendar year; as already mentioned, that this data can be downloaded at https://raw.githubusercontent.com/jakevdp/data-CDCbirths/master/births.csv.\n",
    "\n",
    "本例中的数据是前面章节我们已经用过的（参见[\"例子：出生率\"](03.09-Pivot-Tables.ipynb#Example:-Birthrate-Data)），当时我们对年内的平均出生数据创建了一个图表；就像前面已经提到的，这个数据可以在 https://raw.githubusercontent.com/jakevdp/data-CDCbirths/master/births.csv 下载。\n",
    "\n",
    "> We'll start with the same cleaning procedure we used there, and plot the results:\n",
    "\n",
    "我们先按照前面的方式进行同样的数据清洗程序，然后以图表展示这个结果："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "births = pd.read_csv('data/births.csv')\n",
    "\n",
    "quartiles = np.percentile(births['births'], [25, 50, 75])\n",
    "mu, sig = quartiles[1], 0.74 * (quartiles[2] - quartiles[0])\n",
    "births = births.query('(births > @mu - 5 * @sig) & (births < @mu + 5 * @sig)')\n",
    "\n",
    "births['day'] = births['day'].astype(int)\n",
    "\n",
    "births.index = pd.to_datetime(10000 * births.year +\n",
    "                              100 * births.month +\n",
    "                              births.day, format='%Y%m%d')\n",
    "births_by_date = births.pivot_table('births',\n",
    "                                    [births.index.month, births.index.day])\n",
    "births_by_date.index = [pd.datetime(2012, month, day)\n",
    "                        for (month, day) in births_by_date.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "births_by_date.plot(ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> When we're communicating data like this, it is often useful to annotate certain features of the plot to draw the reader's attention.\n",
    "This can be done manually with the ``plt.text``/``ax.text`` command, which will place text at a particular x/y value:\n",
    "\n",
    "当我们绘制了这样的图表来表达数据时，如果我们能对一些图表的特性作出标注来吸引读者的注意力通常是非常有帮助的。这可以通过调用`plt.text`或`ax.text`函数来实现，它们可以在某个特定的x，y轴位置输出一段文字："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "births_by_date.plot(ax=ax)\n",
    "\n",
    "# 在折线的特殊位置标注文字\n",
    "style = dict(size=10, color='gray')\n",
    "\n",
    "ax.text('2012-1-1', 3950, \"New Year's Day\", **style)\n",
    "ax.text('2012-7-4', 4250, \"Independence Day\", ha='center', **style)\n",
    "ax.text('2012-9-4', 4850, \"Labor Day\", ha='center', **style)\n",
    "ax.text('2012-10-31', 4600, \"Halloween\", ha='right', **style)\n",
    "ax.text('2012-11-25', 4450, \"Thanksgiving\", ha='center', **style)\n",
    "ax.text('2012-12-25', 3850, \"Christmas \", ha='right', **style)\n",
    "\n",
    "# 设置标题和y轴标签\n",
    "ax.set(title='USA births by day of year (1969-1988)',\n",
    "       ylabel='average daily births')\n",
    "\n",
    "# 设置x轴标签月份居中\n",
    "ax.xaxis.set_major_locator(mpl.dates.MonthLocator())\n",
    "ax.xaxis.set_minor_locator(mpl.dates.MonthLocator(bymonthday=15))\n",
    "ax.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax.xaxis.set_minor_formatter(mpl.dates.DateFormatter('%h'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The ``ax.text`` method takes an x position, a y position, a string, and then optional keywords specifying the color, size, style, alignment, and other properties of the text.\n",
    "Here we used ``ha='right'`` and ``ha='center'``, where ``ha`` is short for *horizonal alignment*.\n",
    "See the docstring of ``plt.text()`` and of ``mpl.text.Text()`` for more information on available options.\n",
    "\n",
    "`ax.text`方法接收x位置、y位置、一个字符串和额外可选的关键字参数可以用来设置颜色、大小、样式、对齐等文本格式。上面我们使用了`ha='right'`和`ha='center'`，这里的`ha`是*hirizonal alignment（水平对齐）*的缩写。要查阅更多的可用参数，请查看`plt.text()`和`mpl.text.Text()`的文档字符串内容。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transforms and Text Position\n",
    "\n",
    "## 转换和文本位置\n",
    "\n",
    "> In the previous example, we have anchored our text annotations to data locations. Sometimes it's preferable to anchor the text to a position on the axes or figure, independent of the data. In Matplotlib, this is done by modifying the *transform*.\n",
    "\n",
    "在刚才的例子中，我们将文字标注根据数据位置进行了定位。有些时候我们需要将文字标注独立于数据位置而根据图表位置进行定位。Matplotlib通过*转换*完成这项工作。\n",
    "\n",
    "> Any graphics display framework needs some scheme for translating between coordinate systems.\n",
    "For example, a data point at $(x, y) = (1, 1)$ needs to somehow be represented at a certain location on the figure, which in turn needs to be represented in pixels on the screen.\n",
    "Mathematically, such coordinate transformations are relatively straightforward, and Matplotlib has a well-developed set of tools that it uses internally to perform them (these tools can be explored in the ``matplotlib.transforms`` submodule).\n",
    "\n",
    "任何的图形显示框架都需要在坐标系统之间进行转换的机制。例如，一个数据点位于$(x, y) = (1, 1)$被转换为图表中的某个位置，进而转换为屏幕上显示的像素。这样的坐标转换在数学上都相对来说比较直接，，而且Matplotlib提供了一系列的工具实现了转换（这些工具可以在`matplotlib.transforms`模块中找到）。\n",
    "\n",
    "> The average user rarely needs to worry about the details of these transforms, but it is helpful knowledge to have when considering the placement of text on a figure. There are three pre-defined transforms that can be useful in this situation:\n",
    "\n",
    "> - ``ax.transData``: Transform associated with data coordinates\n",
    "> - ``ax.transAxes``: Transform associated with the axes (in units of axes dimensions)\n",
    "> - ``fig.transFigure``: Transform associated with the figure (in units of figure dimensions)\n",
    "\n",
    "一般来说，用户很少需要关注这些转换的细节，但是当考虑将文本在图表上展示时，这些知识却比较有用。在这种情况中，下面三种定义好的转换是比较有用的：\n",
    "\n",
    "- `ax.transData`：与数据坐标相关的转换\n",
    "- `ax.tranAxes`：与Axes尺寸相关的转换（单位是axes的宽和高）\n",
    "- `ax.tranFigure`：与figure尺寸相关的转换（单位是figure的宽和高）\n",
    "\n",
    "> Here let's look at an example of drawing text at various locations using these transforms:\n",
    "\n",
    "下面我们来看看使用这些转换将文字写在图表中不同位置的例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(facecolor='lightgray')\n",
    "ax.axis([0, 10, 0, 10])\n",
    "\n",
    "# transform=ax.transData是默认的，这里写出来是为了明确对比\n",
    "ax.text(1, 5, \". Data: (1, 5)\", transform=ax.transData)\n",
    "ax.text(0.5, 0.1, \". Axes: (0.5, 0.1)\", transform=ax.transAxes)\n",
    "ax.text(0.2, 0.2, \". Figure: (0.2, 0.2)\", transform=fig.transFigure);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Note that by default, the text is aligned above and to the left of the specified coordinates: here the \".\" at the beginning of each string will approximately mark the given coordinate location.\n",
    "\n",
    "注意默认情况下，文字是在指定坐标位置靠左对齐的：这里每个字符串开始的\".\"的位置就是每种转换的坐标位置。\n",
    "\n",
    "> The ``transData`` coordinates give the usual data coordinates associated with the x- and y-axis labels.\n",
    "The ``transAxes`` coordinates give the location from the bottom-left corner of the axes (here the white box), as a fraction of the axes size.\n",
    "The ``transFigure`` coordinates are similar, but specify the position from the bottom-left of the figure (here the gray box), as a fraction of the figure size.\n",
    "\n",
    "`transData`坐标给定的是通常使用的x和y轴坐标位置。`transAxes`坐标给定的是从axes左下角开始算起（白色区域）的坐标位置，使用的是宽度和长度的占比。`transFigure`坐标类似，给定的是从figure左下角开始算起（灰色区域）的坐标位置，使用的也是宽度和长度的占比。\n",
    "\n",
    "> Notice now that if we change the axes limits, it is only the ``transData`` coordinates that will be affected, while the others remain stationary:\n",
    "\n",
    "因此如果我们改变了轴的最大长度，只有`transData`坐标会收到影响，其他两个还是保持在相同位置："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set_xlim(0, 2)\n",
    "ax.set_ylim(-6, 6)\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This behavior can be seen more clearly by changing the axes limits interactively: if you are executing this code in a notebook, you can make that happen by changing ``%matplotlib inline`` to ``%matplotlib notebook`` and using each plot's menu to interact with the plot.\n",
    "\n",
    "这个变化可以通过动态改变轴的最大长度看的更加清楚：如果你在notebook执行这段代码，你可以将`%matplotlib inline`改为`%matplotlib notebook`，然后使用图表的菜单来交互式的改变图表。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Arrows and Annotation\n",
    "\n",
    "## 箭头和标注\n",
    "\n",
    "> Along with tick marks and text, another useful annotation mark is the simple arrow.\n",
    "\n",
    "除了刻度标签和文字标签，另一种常用的标注是箭头。\n",
    "\n",
    "> Drawing arrows in Matplotlib is often much harder than you'd bargain for.\n",
    "While there is a ``plt.arrow()`` function available, I wouldn't suggest using it: the arrows it creates are SVG objects that will be subject to the varying aspect ratio of your plots, and the result is rarely what the user intended.\n",
    "Instead, I'd suggest using the ``plt.annotate()`` function.\n",
    "This function creates some text and an arrow, and the arrows can be very flexibly specified.\n",
    "\n",
    "在Matplotlib中绘制箭头通常比你想象的难得多。虽然有`plt.arrow()`函数，作者不建议使用它：这个函数绘制的箭头是一个SVG对象，因此在图表使用不同的比例的情况会产生问题，结果通常不能让用户满意。因此，作者建议使用`plt.annotate()`函数。这个函数会绘制一些文字以及一个箭头，并且箭头可以非常灵活的进行配置。\n",
    "\n",
    "> Here we'll use ``annotate`` with several of its options:\n",
    "\n",
    "下面我们提供一些参数来使用`annotate`函数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "x = np.linspace(0, 20, 1000)\n",
    "ax.plot(x, np.cos(x))\n",
    "ax.axis('equal')\n",
    "\n",
    "ax.annotate('local maximum', xy=(6.28, 1), xytext=(10, 4),\n",
    "            arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "\n",
    "ax.annotate('local minimum', xy=(5 * np.pi, -1), xytext=(2, -6),\n",
    "            arrowprops=dict(arrowstyle=\"->\",\n",
    "                            connectionstyle=\"angle3,angleA=0,angleB=-90\"));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The arrow style is controlled through the ``arrowprops`` dictionary, which has numerous options available.\n",
    "These options are fairly well-documented in Matplotlib's online documentation, so rather than repeating them here it is probably more useful to quickly show some of the possibilities.\n",
    "Let's demonstrate several of the possible options using the birthrate plot from before:\n",
    "\n",
    "箭头的样式是使用`箭头属性`字典值进行控制的，里面有很多可用的参数。这些参数在Matplotlib的在线文档中已经有了很详细的说明，因此在这里就不将这部分内容重复介绍一遍了。我们在前面出生率图上再使用一些参数进行更多的说明："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "births_by_date.plot(ax=ax)\n",
    "\n",
    "# 为图表添加标注\n",
    "ax.annotate(\"New Year's Day\", xy=('2012-1-1', 4100),  xycoords='data',\n",
    "            xytext=(50, -30), textcoords='offset points',\n",
    "            arrowprops=dict(arrowstyle=\"->\",\n",
    "                            connectionstyle=\"arc3,rad=-0.2\"))\n",
    "\n",
    "ax.annotate(\"Independence Day\", xy=('2012-7-4', 4250),  xycoords='data',\n",
    "            bbox=dict(boxstyle=\"round\", fc=\"none\", ec=\"gray\"),\n",
    "            xytext=(10, -40), textcoords='offset points', ha='center',\n",
    "            arrowprops=dict(arrowstyle=\"->\"))\n",
    "\n",
    "ax.annotate('Labor Day', xy=('2012-9-4', 4850), xycoords='data', ha='center',\n",
    "            xytext=(0, -20), textcoords='offset points')\n",
    "ax.annotate('', xy=('2012-9-1', 4850), xytext=('2012-9-7', 4850),\n",
    "            xycoords='data', textcoords='data',\n",
    "            arrowprops={'arrowstyle': '|-|,widthA=0.2,widthB=0.2', })\n",
    "\n",
    "ax.annotate('Halloween', xy=('2012-10-31', 4600),  xycoords='data',\n",
    "            xytext=(-80, -40), textcoords='offset points',\n",
    "            arrowprops=dict(arrowstyle=\"fancy\",\n",
    "                            fc=\"0.6\", ec=\"none\",\n",
    "                            connectionstyle=\"angle3,angleA=0,angleB=-90\"))\n",
    "\n",
    "ax.annotate('Thanksgiving', xy=('2012-11-25', 4500),  xycoords='data',\n",
    "            xytext=(-120, -60), textcoords='offset points',\n",
    "            bbox=dict(boxstyle=\"round4,pad=.5\", fc=\"0.9\"),\n",
    "            arrowprops=dict(arrowstyle=\"->\",\n",
    "                            connectionstyle=\"angle,angleA=0,angleB=80,rad=20\"))\n",
    "\n",
    "\n",
    "ax.annotate('Christmas', xy=('2012-12-25', 3850),  xycoords='data',\n",
    "             xytext=(-30, 0), textcoords='offset points',\n",
    "             size=13, ha='right', va=\"center\",\n",
    "             bbox=dict(boxstyle=\"round\", alpha=0.1),\n",
    "             arrowprops=dict(arrowstyle=\"wedge,tail_width=0.5\", alpha=0.1));\n",
    "\n",
    "# 设置图表标题和坐标轴标记\n",
    "ax.set(title='USA births by day of year (1969-1988)',\n",
    "       ylabel='average daily births')\n",
    "\n",
    "# 设置月份坐标居中显示\n",
    "ax.xaxis.set_major_locator(mpl.dates.MonthLocator())\n",
    "ax.xaxis.set_minor_locator(mpl.dates.MonthLocator(bymonthday=15))\n",
    "ax.xaxis.set_major_formatter(plt.NullFormatter())\n",
    "ax.xaxis.set_minor_formatter(mpl.dates.DateFormatter('%h'));\n",
    "\n",
    "ax.set_ylim(3600, 5400);"
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    "> You'll notice that the specifications of the arrows and text boxes are very detailed: this gives you the power to create nearly any arrow style you wish.\n",
    "Unfortunately, it also means that these sorts of features often must be manually tweaked, a process that can be very time consuming when producing publication-quality graphics!\n",
    "Finally, I'll note that the preceding mix of styles is by no means best practice for presenting data, but rather included as a demonstration of some of the available options.\n",
    "\n",
    "上图中箭头和文字框都非常详尽了：可以看出你几乎可以使用`plt.annotate`创建任何你想要的箭头样式。不幸的是，这意味着这种特性都需要手工进行调整，因此如果需要获得印刷质量的图像，这将是一个非常耗费时间的工作。最后，必须指出，上述这种多种样式混合的方式来展现数据肯定不是最佳实践，这里只是为了尽可能多的介绍可用的参数。\n",
    "\n",
    "> More discussion and examples of available arrow and annotation styles can be found in the Matplotlib gallery, in particular the [Annotation Demo](http://matplotlib.org/examples/pylab_examples/annotation_demo2.html).\n",
    "\n",
    "更多关于Matplotlib的箭头和标注样式的讨论和例子可以访问Matplotlib gallery，特别是[标注演示](http://matplotlib.org/examples/pylab_examples/annotation_demo2.html)。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [多个子图表](04.08-Multiple-Subplots.ipynb) | [目录](Index.ipynb) | [自定义刻度](04.10-Customizing-Ticks.ipynb) >\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/wangyingsm/Python-Data-Science-Handbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open and Execute in Google Colaboratory\"></a>\n"
   ]
  }
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